Atul Khiste
Head of Product
Atul, a seasoned product leader, brings a wealth of experience in the manufacturing and technology industries. With a proven track record of building and scaling innovative SAAS products, Atul has successfully led the development of multi-million dollar businesses.`
Atul's approach is characterized by a strong emphasis on data-driven decision-making and a deep understanding of customer needs.
He leverages data insights to identify opportunities for improvement and to develop products that deliver real value. This customer-centric focus has consistently resulted in successful product launches and significant business impact.
Start by defining specific, measurable objectives that align directly with the business goals. By setting Key Performance Indicators (KPIs) from the outset, the project can remain focused on delivering concrete business value.
Conducting a smaller-scale proof of concept allows organizations to validate the solution’s ROI and resolve potential challenges early. Starting with a pilot area where quick wins are achievable helps gain stakeholder confidence and secures further support for broader rollout.
A dedicated champion on the manufacturing side should ensure accountability and alignment between the manufacturing team and software provider. This role facilitates decision-making, removes obstacles, and allows the provider to focus on delivering value without delays from indecision or unauthorized team members.
Both the manufacturer and solution provider should collaboratively establish specific, measurable objectives. For example, if the client aims to reduce machine downtime, define KPIs that measure downtime reduction. This shared clarity helps both parties focus on meaningful results and prevents misunderstandings about project success.
This includes mapping out the most impactful use cases specific to your factory that can drive immediate improvements. Also, a comprehensive assessment of the readiness of the workforce and systems for adopting advanced technologies is critical to designing the first few steps.
These strategies ensure that both sides remain aligned and responsive, increasing the chances of a successful PoC that delivers clear value.
Look for a provider that enables plug-and-play data collection and requires minimal manual intervention.
Choose a solution that can grow with the business, adapting to changes in production needs, and offering customization options for specific operational requirements, ensuring long-term alignment with business goals.
Select providers with proven experience in manufacturing to ensure they understand industry challenges and can tailor solutions effectively.
Opt for providers that offer a responsive service model for ongoing support and maintenance.
Prioritize a provider committed to innovation, with solutions that incorporate AI and advanced analytics to provide automated, actionable insights—going beyond traditional reports to add real operational value.
When choosing IIoT solutions, opt for providers who adhere to industry open standards like OPC UA (Open Platform Communications Unified Architecture) and MQTT (Message Queuing Telemetry Transport). These standards facilitate communication across different devices and platforms, allowing data to flow freely between systems.
Middleware can act as a bridge between new IIoT platforms and legacy systems, translating data and ensuring compatibility. This approach helps reduce integration costs and allows existing systems to “speak” with newer technology.
Select IIoT providers that offer modular and scalable solutions, which can be implemented in phases and customized to fit specific operational needs. This modularity allows for incremental integration, reducing the risks associated with large-scale implementations .
To bridge the gap between client expectations and actual IIoT solution outcomes during the Proof of Concept (PoC) phase, focusing on clear alignment and iterative testing can make a significant difference.
Both the manufacturer and solution provider should collaboratively establish specific, measurable objectives. For example, if the client aims to reduce machine downtime, define KPIs that measure downtime reduction. This shared clarity helps both parties focus on meaningful results and prevents misunderstandings about project success.
This includes mapping out the most impactful use cases specific to your factory that can drive immediate improvements. Also, a comprehensive assessment of the readiness of the workforce and systems for adopting advanced technologies is critical to designing the first few steps. These strategies ensure that both sides remain aligned and responsive, increasing the chances of a successful PoC that delivers clear value.
To bridge the gap between client expectations and actual IIoT solution outcomes during the Proof of Concept (PoC) phase, focusing on clear alignment and iterative testing can make a significant difference.
Linecraft provides thorough onboarding and training sessions tailored to each client's needs. This includes hands-on guidance, interactive tutorials, and access to a dedicated support team, ensuring that clients are well-equipped to operate and optimize the system from day one.
To maintain momentum post-implementation, Linecraft offers ongoing support with a resource library, including training videos, webinars, and troubleshooting guides. Additionally, we provide access to a dedicated customer success manager to address any challenges, enabling clients to continuously improve their operations with confidence.
By focusing on interoperability, low-touch automation, and strong customer support, Linecraft minimizes integration complexities and empowers clients to fully leverage the benefits of IIoT, regardless of their starting point in the digital transformation journey.
Measures productivity by tracking equipment availability, performance, and quality rates.
Measures reductions in energy usage, showing cost savings and sustainability improvements.
Tracks decreases in unplanned downtime, indicating effective predictive maintenance.
Monitors production rate improvements, demonstrating increased output and capacity.
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Tracks the time per production cycle to assess speed and identify areas for efficiency gains.
Identifies production delays or constraints, guiding targeted improvements in the workflow.
Monitors system usage to ensure effective engagement from operators and staff in the IIoT platform.
Measures the defect rate, helping to monitor improvements in product quality from IIoT insights.
Tracks cost reductions in maintenance, showcasing benefits of predictive analytics and proactive monitoring.
Measures how quickly issues identified by IIoT are addressed, highlighting responsiveness in operations.
For manufacturers just starting their IIoT transformation, my advice is to begin with a single, well-defined problem—one where the impact of solving (or not solving) it is clear and measurable. Concentrate your efforts on this specific issue and select a solution or provider with proven expertise in addressing it. Provide the necessary support to ensure they can deliver a solution within a defined timeline.
As you move forward, identify a champion within the organization who will be accountable for these improvements. This individual will help ensure the solution becomes embedded within your processes, rather than remaining a one-off project. Once this initial issue is resolved, take on the next two specific problems. Use the insights from the first project to scale IIoT capabilities from one area to another, rather than attempting a broad, generalized approach. This staged strategy fosters sustainable, organization-wide IIoT adoption.
